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Finally, for some problems, the major feature of the concurrency is the presence of well defined interacting groups of tasks, and the key issue is how the data flows among the tasks For example, in a signal processing application, data may flow through a sequence of tasks organized as a pipeline, each performing a transformation on successive data elements Or a discrete event simulation might be parallelized by decomposing it into a tasks interacting via "events" Here, the major feature of the concurrency is the way in which these distinct task groups interact Notice also that the most effective parallel algorithm design might make use of multiple algorithm structures (combined hierarchically, compositionally, or in sequence), and this is the point at which to consider whether such a design makes sense For example, it often happens that the very top level of the design is a sequential composition of one or more Algorithm Structure patterns Other designs might be organized hierarchically, with one pattern used to organize the interaction of the major task groups and other patterns used to organize tasks within the groups for example, an instance of the Pipeline pattern in which individual stages are instances of the Task Parallelism pattern 423 The Algorithm Structure Decision T ree For each subset of tasks, which Algorithm Structure design pattern most effectively defines how to map the tasks onto UEs Having considered the questions raised in the preceding sections, we are now ready to select an algorithm structure, guided by an understanding of constraints imposed by the target platform, an appreciation of the role of hierarchy and composition, and a major organizing principle for the problem The decision is guided by the decision tree shown in Fig 42 Starting at the top of the tree, consider the concurrency and the major organizing principle, and use this information to select one of the three branches of the tree; then follow the upcoming discussion for the appropriate subtree Notice again that for some problems, the final design might combine more than one algorithm structure: If no single structure seems suitable, it might be necessary to divide the tasks making up the problem into two or more groups, work through this procedure separately for each group, and then determine how to combine the resulting algorithm structures. how to write pdf file in asp.net c# How to Easily Create a PDF Document in ASP . NET Core Web API
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What is the best way to send data from a database to a pdf writer ? Example: database -> c# object -> xml + xslt -> pdf writer or database ->c# ... Select the Organize By Tasks branch when the execution of the tasks themselves is the best organizing principle Then determine how the tasks are enumerated If they can be gathered into a set linear in any number of dimensions, choose the Task Parallelism pattern This pattern includes both situations in which the tasks are independent of each other (so called embarrassingly parallel algorithms) and situations in which there are some dependencies among the tasks in the form of access to shared data or a need to exchange messages If the tasks are enumerated by a recursive procedure, choose the Divide and Conquer pattern In this pattern, the problem is solved by recursively dividing it into subproblems, solving each subproblem independently, and then recombining the subsolutions into a solution to the original problem SELECT * FROM users WHERE `last-name` = 'Smith' PushBackInputStream(InputStream input) creates a PushBackInputStream that will read from the specified input stream PushBackInputStream(InputStream input int bufferSize) throws javalangIllegalArgumentException creates a PushBackInputStream Select the Organize By Data Decomposition branch when the decomposition of the data is the major organizing principle in understanding the concurrency There are two patterns in this group, differing in how the decomposition is structured linearly in each dimension or recursively Choose the Geometric Decomposition pattern when the problem space is decomposed into discrete subspaces and the problem is solved by computing solutions for the subspaces, with the solution for each subspace typically requiring data from a small number of other subspaces Many instances of this pattern can be found in scientific computing, where it is useful in parallelizing grid based computations, for example Choose the Recursive Data pattern when the problem is defined in terms of following links through a recursive data structure (for example, a binary tree) that will read from an input stream and use a buffer of the specified size If a value of less than one is specified for the buffer size, an exception will be thrown When using this Select expression, only those items having an attribute named lastname with a value of Smith are returned Here, the equals operator is used in a single comparisonThere are a dozen other operators that you can use, and you can combine multiple comparisons in a single queryThe WHERE clause really forms the heart of the Select expression, determining the exact set of return itemsA detailed discussion of the available operators and how they are used in the context of comparisons occurs later in this chapter Notice that both the attribute name and the attribute value are quoted in the preceding example But also notice that they are quoted using a different characterAttribute names used in a WHERE clause are subject to the Select quoting rules for namesAttribute values, on the other hand, are subject to the Select quoting rules for values asp.net pdf writer PDF - Writer .NET - Generate PDF from WinFrom .NET, ASP . NET ...
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